基于图像技术的迷彩面料颜色测量

颜色测量对于迷彩面料的色彩分析、产品设计、质量控制有着重要的指导意义。针对由织物组织纹理和图案的多样性造成测色难度增大的问题,提出一种迷彩面料图案分割的方法,并提取色彩信息加以分析。利用数码相机进行迷彩面料图像的采集,利用Mean Shift聚类算法将图像分割成不同颜色的色块,再用神经网络回归实现图像从RGB(red,green,blue)颜色空间到Lab颜色空间的转换,并通过正态分布法对迷彩颜色进行分析测量。试验结果表明:提出的图像处理方法可实现迷彩服面料颜色的自动分割;与Datacolor分光测色仪测色结果相比,正态分布法分析得到的平均色差不超过2。

Color Measurement of Camouflage Fabric Based on Image Technology

Color measurement is important for color analysis,product design and quality control of camouflage fabric.Aiming at the problem of the increasing difficulty in color measurement caused by diversity of fabric texture and pattern,a method for image segmentation,color information extraction and analysis of camouflage fabric was proposed.Digital camera was used to collect the camouflage fabric image,and Mean Shift clustering algorithm was used to segment the color blocks.The image was transformed from RGB(red,green,blue)color space to Lab color space by neural network regression,and the color of camouflage was analyzed and measured by normal distribution method.The experimental results show that the image processing method can realize the automatic segmentation of camouflage fabric color,and compared with the Datacolor spectrophotometer color measurement,the average color aberration obtained by normal distribution method is less than 2.